Learning to Solve the AC-OPF using Sensitivity-Informed Deep Neural Networks

27 March 2021

Papers citing "Learning to Solve the AC-OPF using Sensitivity-Informed Deep Neural Networks"

22 / 22 papers shown

Title
A Data-Driven Real-Time Optimal Power Flow Algorithm Using Local Feedback Heng Liang Yujin Huang Changhong Zhao 65 0 0 24 Feb 2025
Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow S. Pineda Juan Pérez-Ruiz J. Morales AI4CE 51 0 0 28 Jan 2025
Generative Edge Detection with Stable Diffusion Caixia Zhou Yaping Huang Mochu Xiang Jiahui Ren Haibin Ling Jing Zhang 59 0 0 04 Oct 2024
Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency Yuqi Zhou Hao Zhu 26 1 0 09 May 2024
QCQP-Net: Reliably Learning Feasible Alternating Current Optimal Power Flow Solutions Under Constraints Sihan Zeng Youngdae Kim Yuxuan Ren Kibaek Kim 47 2 0 11 Jan 2024
Operational risk quantification of power grids using graph neural network surrogates of the DC OPF Yadong Zhang Pranav M. Karve Sankaran Mahadevan AI4CE 18 0 0 07 Nov 2023
Physics-Guided Graph Neural Networks for Real-time AC/DC Power Flow Analysis Meiying Yang Gao Qiu Yonghuang Wu Junyong Liu Nina Dai Yue Shui Kai Liu Lijie Ding AI4CE 14 1 0 29 Apr 2023
An Efficient Learning-Based Solver for Two-Stage DC Optimal Power Flow with Feasibility Guarantees Ling Zhang Daniel Tabas Baosen Zhang 9 4 0 03 Apr 2023
Enriching Neural Network Training Dataset to Improve Worst-Case Performance Guarantees Rahul Nellikkath Spyros Chatzivasileiadis 36 3 0 23 Mar 2023
Optimal Power Flow Based on Physical-Model-Integrated Neural Network with Worth-Learning Data Generation Zuntao Hu Hongcai Zhang AI4CE 32 6 0 10 Jan 2023
Minimizing Worst-Case Violations of Neural Networks Rahul Nellikkath Spyros Chatzivasileiadis 38 3 0 21 Dec 2022
Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes Milena Mitrović A. Lukashevich Petr Vorobev Vladimir Terzija Yury Maximov Deepjyoti Deka 24 1 0 30 Aug 2022
Data-Driven Stochastic AC-OPF using Gaussian Processes M. Mitrovic A. Lukashevich Petr Vorobev Vladimir Terzija S. Budenny Yury Maximov Deepjoyti Deka 30 4 0 21 Jul 2022
Topology-aware Graph Neural Networks for Learning Feasible and Adaptive ac-OPF Solutions Shaohui Liu Chengyang Wu Hao Zhu 35 47 0 16 May 2022
Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems Jochen Stiasny Samuel C. Chevalier Rahul Nellikkath Brynjar Sævarsson Spyros Chatzivasileiadis 29 14 0 14 Mar 2022
DNN-based Policies for Stochastic AC OPF Sarthak Gupta Sidhant Misra Deepjyoti Deka V. Kekatos 34 13 0 04 Dec 2021
Power Flow Balancing with Decentralized Graph Neural Networks Jonas Berg Hansen S. N. Anfinsen F. Bianchi 31 34 0 03 Nov 2021
OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets Trager Joswig-Jones K. Baker Ahmed S. Zamzam 15 25 0 01 Nov 2021
Learning to Solve the AC Optimal Power Flow via a Lagrangian Approach Ling Zhang Baosen Zhang 22 8 0 04 Oct 2021
Physics-Informed Neural Networks for Minimising Worst-Case Violations in DC Optimal Power Flow Rahul Nellikkath Spyros Chatzivasileiadis PINN 15 32 0 28 Jun 2021
Controlling Smart Inverters using Proxies: A Chance-Constrained DNN-based Approach Sarthak Gupta V. Kekatos Ming Jin 32 20 0 02 May 2021
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods Ferdinando Fioretto Terrence W.K. Mak Pascal Van Hentenryck AI4CE 81 199 0 19 Sep 2019